Multi-Omics of Pine Wood Nematode Pathogenicity Associated With Culturable Associated Microbiota Through an Artificial Assembly Approach

Abstract

Pinewood nematode (PWN), the causal agent of pine wilt disease (PWD), causes massive global losses of Pinus species each year. Bacteria and fungi existing in symbiosis with PWN are closely linked with the pathogenesis of PWD, but the relationship between PWN pathogenicity and the associated microbiota is still ambiguous. This study explored the relationship between microbes and the pathogenicity of PWN by establishing a PWN-associated microbe library, and used this library to generate five artificial PWN–microbe symbiont (APMS) assemblies with gnotobiotic PWNs. The fungal and bacterial communities of different APMSs (the microbiome) were explored by next-generation sequencing. Furthermore, different APMSs were used to inoculate the same Masson pine (Pinus massoniana) cultivar, and multi-omics (metabolome, phenomics, and transcriptome) data were obtained to represent the pathogenicity of different APMSs at 14 days post-inoculation (dpi). Significant positive correlations were observed between microbiome and transcriptome or metabolome data, but microbiome data were negatively correlated with the reactive oxygen species (ROS) level in the host. Five response genes, four fungal genera, four bacterial genera, and nineteen induced metabolites were positively correlated with the ROS level, while seven induced metabolites were negatively correlated. To further explore the function of PWN-associated microbes, single genera of functional microbes (Mb1–Mb8) were reloaded onto gnotobiotic PWNs and used to inoculate pine tree seedlings. Three of the genera (Cladophialophora, Ochroconis, and Flavobacterium) decreased the ROS level of the host pine trees, while only one genus (Penicillium) significantly increased the ROS level of the host pine tree seedlings. These results demonstrate a clear relationship between associated microbes and the pathogenicity of PWN, and expand the knowledge on the interaction between PWD-induced forest decline and the PWN-associated microbiome.

Bacteria‐induced amino acid metabolism involved in appearance characteristics of high‐temperature Daqu

“…Metabolites were analyzed using principal component analysis (PCA) and orthogonal partial least-squares discriminate analysis (OPLS-DA) using the R package metaX (version 4.1.1). 15 KEGG (http://www.kegg.jp) database were utilized to search for the pathways of metabolites. 16 The correlation analysis between dominant genus and metabolites was revealed by R package psych and pheatmap (version 4.1.1), 17 and other figures were drawn using the R diagram packages.…”

“…Physicochemical properties among different HTD samples were tested by conducting a one‐way analysis of variance (ANOVA) followed by Duncan's test using SPSS (version 20.0; SPSS, Chicago, IL, USA) and P < 0.05 were considered significant. Metabolites were analyzed using principal component analysis (PCA) and orthogonal partial least‐squares discriminate analysis (OPLS‐DA) using the R package metaX (version 4.1.1) 15 . KEGG (http://www.kegg.jp) database were utilized to search for the pathways of metabolites 16 .…”

Gene sdaB Is Involved in the Nematocidal Activity of Enterobacter ludwigii AA4 Against the Pine Wood Nematode Bursaphelenchus xylophilus

“…Chemical insecticides and nematicides used to control B. xylophilus by jet-sprays or trunk injections for decades (Qiu et al, 2019;Guo et al, 2020;Faria et al, 2021) have become a major social concern. More environmental-friendly strategies, such as beneficial microorganisms that suppress PWN, have recently gained more attention (Tian et al, 2007;Wu et al, 2013;Cai et al, 2022).…”

Integrated transcriptomic and metabolic analyses provide insights into the maintenance of embryogenic potential and the biosynthesis of phenolic acids and flavonoids involving transcription factors in Larix kaempferi (Lamb.) Carr.

“…The combined analysis of transcriptome and metabolome data can be used to predict the gene function involved in the targeted metabolic pathway and simultaneously provide supporting information for gene mining ( Fukushima et al., 2009 ). In conifers, the integrated analysis of the two omics were used in several species such as Pinus pinaster ( Cañas et al., 2015 ), Pinus radiata ( Escandón et al., 2017 ), P. abies ( Dobrowolska et al., 2017 ; Blokhina et al., 2019 ), Pinus taeda ( Mao et al., 2021 ), Pinus massoniana ( Cai et al., 2021 ), and L. olgensis ( Zhang et al., 2021b ) to address the regulatory mechanisms underlying some problems in plant systems biology including tree responses to environmental changes or disease, the biosynthesis of targeted metabolites, and somatic embryo germination. Given the fact that SE induction is an initiation phase regulated by a complex network of numerous genes ( Mordhorst et al., 1997 ; Wang et al., 2020 ), there must also be many metabolic activities functioning in this process, which can be reflected by the differences between EC and NEC.…”